Optimal multi-robot path planning for pesticide spraying in agricultural fields

Lal, Ratan; Sharda, Ajay; Prabhakar, Pavithra

doi:10.1109/cdc.2017.8264538

Cited by 16 publications

(10 citation statements)

References 20 publications

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“…As the work can be carried out more efficiently, potential for utilization is increasing through many related studies [17]. In agriculture, multi-robots are currently being utilized in various applications such as mapping [18], [19], seeding [20], sensing [21], [22], and pesticide spraying [23], [24].…”

Section: Introductionmentioning

confidence: 99%

A Voronoi Diagram-Based Workspace Partition for Weak Cooperation of Multi-Robot System in Orchard

Kim

Son

2020

IEEE Access

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Nowadays, multi-robot systems are being utilized to perform agricultural tasks. It is particularly essential to robotize pesticide spraying because of the risk of poisoning workers. However, the problem is that the human-driven sprayers are big size, and difficult to maneuver in many orchards. Therefore, heavy spraying robots must be replaced with lighter robots. Also, it takes a lot of times to perform spraying using only one sprayer in a large orchard. To achieve this goal, the multi-robot system (MRS) can be applied to the spraying by robot cooperation to improve performance. In this study, we developed a task allocation system based on a Voronoi diagram for a multi-robot spraying system in an orchard. The seed point for area partition using the Voronoi diagram was obtained through node clustering using a k-means clustering algorithm. In the experiment, workspaces were partitioned according to the number of robots, from 2 to 10. A total of four metrics were used to evaluate the performance of the system. The results confirmed that our task allocation system is applicable to real orchards. INDEX TERMS Agricultural robot, multi-robot system, task allocation, area partition, unmanned ground vehicle (UGV).

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Section: Introductionmentioning

confidence: 99%

A Voronoi Diagram-Based Workspace Partition for Weak Cooperation of Multi-Robot System in Orchard

Kim

Son

2020

IEEE Access

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“…Visible brightness symbolizes just a small fraction of the electromagnetic spectrum. It varies in wavelength starting with 3.9 × 10 −7 m (violet) to 7.5 × 10 −7 m (red), and has corresponding frequencies that vary beginning with 7.9 × 10 14 to 4 × 10 14 .…”

Section: E Electromagnetic Spectrummentioning

confidence: 99%

“…With the assistance of Artificial Intelligence, information is assembled to keep verification records on weeds, which aid the ranchers to use pesticides exactly where the plants are located [13]. is diminished the use of the synthetic product splash in a desired sector [14]. As a result, Artificial Intelligence reduces herbicide use in the area relative to the amount of synthetic substances regularly sprayed [15].…”

Section: Introductionmentioning

confidence: 99%

Usage of Artificial Intelligence and Remote Sensing as Efficient Devices to Increase Agricultural System Yields

Ennouri

Smaoui

Gharbi

et al. 2021

Journal of Food Quality

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Artificial Intelligence is an emerging technology in the field of agriculture. Artificial Intelligence-based tools and equipment have actually taken the agriculture sector to a different level. This new technology has improved crop production and enhanced instantaneous monitoring, processing, and collection. The most recent computerized structures using remote sensing and drones have made a significant contribution to the agro-based domain. Moreover, remote sensing has the capability to support the development of farming applications with the aim of facing this main defy, via giving cyclic records on yield status during studied periods at diverse degrees and for diverse parameters. Various hi-tech, computer-supported structures are created to determine different central factors such as plant detection, yield recognition, crop quality, and several other methods. This paper includes the techniques employed for the analysis of collected information in order to enhance the productivity, forecast eventual threats, and reduce the task load on cultivators.

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“…Otro trabajo que presenta un desarrollo de un algoritmo MILP es (180). El objetivo de dicha investigación es generar una planicación de rutas óptima para un enjambre destinado a la fumigación en campos agrícolas.…”

Section: Programa Lineal De Enteros Mixtosunclassified

Obstacle Avoidance Manager for UAVs Swarm

Madridano

Al-Kaff

Flores³

et al. 2020

2020 International Conference on Unmanned Aircraft Systems (ICUAS)

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En primer lugar, agradecer a mis directores académicos, Arturo y David y, a Pablo en Drone Hopper, por acompañarme a lo largo de esta etapa que hoy está más cerca de culminarse. Gracias por la ayuda prestada, por hacerme crecer, en el ámbito profesional y en el personal. Gracias por conar en mí y permitir que, junto a Drone Hopper, haya podido cerrar una etapa tan importante.Aunque si algo me ha llevado hoy a escribir estas líneas es formar parte, durante 5 años, de una familia como el LSI, incluida esa nueva generación de chavalitos, que han hecho del B16 un lugar donde nuca sentirse solo. El principal culpable de ello es Fernando. Fue él quien me brindó la oportunidad de trabajar con gente tan buena como la que aquí trabaja y ha trabajado, porque echando la vista atrás, no puedo olvidarme de personas cómo Noelia, Ricardo o Dani con las que ha sido un verdadero placer trabajar y, que junto al resto, han contribuido a que cada día uno se sienta afortunado de formar parte de un grupo humano como este.Dentro de esta gran familia hay otra persona que merece una mención aparte, no es otro que Abdulla, un amigo más que un compañero de trabajo. Sólo él sabe lo duro que, durante muchos momentos, ha sido esto y, sus palabras, su ayuda y su trabajo han hecho posible que las dudas se despejaran y continuara trabajando por llegar hoy a escribir estas líneas.Al escribir estas líneas no puedo olvidarme de un grupo de personas que durante esta etapa han sido más que compañeros de trabajo, han sido amigos, aquellas personas con las que compartir las alegrías y penas del día a día, gente como Carlos, María, Irene, Fran o Jorge que me han ayudado y apoyado de manera especial a lo largo de esta dura etapa, la cual Jorge advirtió y yo no hice caso.Tampoco puedo terminar este párrafo sin agradecer a Sergio y Alejandro todo el trabajo de estos últimos meses, por hacer más fácil y llevadera la vuelta a la normalidad y por estar codo con codo en las últimas fases de este trabajo.Por último, gracias a mi verdadera familia, a unos padres y hermanas que han sido un espejo dónde mirarse, a los que les debo y, sin los cuáles, no habría llegado hoy a escribir este trabajo. Y gracias a ti, Olga, por comprenderme, soportarme y ayudarme en estos duros meses y, sobre todo, por dar sentido a mi vida de la manera en la que lo has hecho.

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Optimal multi-robot path planning for pesticide spraying in agricultural fields

Cited by 16 publications

References 20 publications

A Voronoi Diagram-Based Workspace Partition for Weak Cooperation of Multi-Robot System in Orchard

A Voronoi Diagram-Based Workspace Partition for Weak Cooperation of Multi-Robot System in Orchard

Usage of Artificial Intelligence and Remote Sensing as Efficient Devices to Increase Agricultural System Yields

Obstacle Avoidance Manager for UAVs Swarm

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